The Bundesanstalt für Materialforschung und -prüfung (BAM) is a senior scientific and technical Federal institute with responsibility to the Federal Ministry for Economic Affairs and Climate Action in Germany. It tests, researches and advises to protect people, the environment and material goods. Their work covers a broad array of topics in the focus areas of energy, infrastructure, environment, materials, and analytical sciences.
BAM is looking for Postdoctoral researcher in machine learning for materials science for a temporary contract of 36 months.
Responsibilities
You will be responsible to develop and advance your own machine learning projects and to closely collaborate with materials scientists. In detail, this includes the following aspects:
Development of new machine learning models for applications in materials science
Implementation of machine learning models in pytorch and other relevant software libraries
Preparation of training data as well as development and selection of suitable features
Visualization and interpretation of results from predictions
Supervision of junior researchers
Communication of research results at scientific conferences and in peer-reviewed journals
Required Qualifications
Successfully completed university studies (diploma/master's degree) as well as a very good doctorate in computer science, technical software development, bioinformatics, mathematics, physics, data engineering or comparable
Very good knowledge of software libraries for data science (e.g., PyTorch, PyTorch-Geometric, Pandas, Scitkit-Learn)
Very good knowledge of the theory and practice of modern machine learning methods (e.g., invertible neural networks and graph neural networks)
Very good knowledge of at least one programming language (e.g., Python, Rust, Go)
Good knowledge of methods for visualizing complex data sets
Experience with version control systems (e.g., Git) is desirable
Experience with statistical methods is desirable
Knowledge of methods for processing and analyzing large amounts of data is desirable
Experience with data from the field of materials science or engineering or natural sciences is desirable
Excellent oral and written language skills/expressiveness in English
Excellent communication and interpersonal skills
Application Procedure
Qualified and interested candidates are invited to apply online through the online application portal.
• Application Deadline: 04.07.2024
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